hand3d's Introduction

ColorHandPose3D network

ColorHandPose3D is a Convolutional Neural Network estimating 3D Hand Pose from a single RGB Image. See the project page for the dataset used and additional information.

Usage

The network ships with a minimal example, that performs a forward pass and shows the predictions.

Download data and unzip it into the projects root folder (This will create 3 folders: "data", "results" and "weights")
run.py - Will run a forward pass of the network on the provided examples

You can compare your results to the content of the folder "results", which shows the predictions we get on our system.

Recommended system

Recommended system (tested):

Ubuntu 16.04.2 (xenial)
Tensorflow 0.11.0 RC0 GPU build with CUDA 8.0.44 and CUDNN 5.1
Python 3.5.2

Python packages used by the example provided and their recommended version:

tensorflow==0.11.0rc0
numpy==1.11.3
scipy==0.18.1
matplotlib==1.5.3

License and Citation

This project is licensed under the terms of the GPL v2 license. By using the software, you are agreeing to the terms of the license agreement.

Please cite us in your publications if it helps your research:

@TechReport{zb2017hand,
  author    = {Christian Zimmermann and Thomas Brox},
  title     = {Learning to Estimate 3D Hand Pose from Single RGB Images},
  institution    = {arXiv:1705.01389},
  year      = {2017},
  note         = "https://arxiv.org/abs/1705.01389",
  url          = "https://lmb.informatik.uni-freiburg.de/projects/hand3d/"
}

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